Method and apparatus for generating raster map

ABSTRACT

A method, apparatus, and computer readable medium for generating a raster map are provided. The method includes generating a first raster map having a first resolution based on acquired laser point cloud. The method further includes generating a second raster map having a second resolution by merging rasters in the first raster map, the second resolution being lower than the first resolution. In addition, the method further includes storing the first raster map and an association between the first raster map and the second raster map. Some embodiments of the present disclosure are capable of meeting different levels of navigation or positioning requirements by generating raster maps of multiple resolutions. Furthermore, some embodiments of the present disclosure store only the raster map having the highest resolution and the association between the various levels of maps, thereby saving the storage space.

CROSS-REFERENCE TO RELATED APPLICATIONS

This disclosure claims priority to Chinese Patent Application no.201711485401.0, filed in China on Dec. 29, 2017, the contents of whichare incorporated herein by reference in their entirety.

TECHNICAL FIELD

Embodiments of the present disclosure generally relate to the field ofelectronic map technology, and more specifically to a method andapparatus for generating a raster map.

BACKGROUND

Electronic maps refer to maps in digital form generated using computingtechnologies, which may be widely used in scenarios such as querying,positioning, and navigating. The electronic maps are generally dividedinto ordinary navigation maps and high-precision maps. The ordinarynavigation maps are user-oriented maps that provide visual interfacesfor querying by users and displaying, while the high-precision maps aremachine-oriented map data that may be used for such as autonomousdriving, robot navigation and positioning. The ordinary navigation mapsare usually obtained by satellite mapping, and their accuracies areusually not high (for example, the error can be several meters or eventens of meters). The high-precision maps are high-precision map datathat not only are highly accurate, but also include other informationthat may be used for precise navigation and positioning, such as laneline information, object height information, and road shape information.

A raster map is a commonly used form of high-precision map that dividesan environment into a series of rasters, where each raster is markedwith a value indicating whether the raster is occupied. That is, theraster map is a product of digital rasterization of a real environmentthat identifies obstacles in the environment by determining whether theraster is occupied. Out of the demand for the navigation and positioningof autonomous vehicles and robots, the raster map describing theoccupation is widely used in the navigation and positioning scenariosfor driverless vehicles and intelligent robots.

SUMMARY

According to illustrative embodiments of the present disclosure, asolution for generating a raster map is provided.

In a first aspect, the present disclosure provides a method forgenerating a raster map. The method includes generating a first rastermap having a first resolution based on acquired laser point cloud. Themethod further includes generating a second raster map having a secondresolution by merging rasters in the first raster map, the secondresolution being lower than the first resolution. In addition, themethod further includes storing the first raster map and an associationbetween the first raster map and the second raster map.

In a second aspect, the present disclosure provides an apparatus forgenerating a raster map. The apparatus includes: a first map generationmodule, configured to generate a first raster map having a firstresolution based on acquired laser point cloud. In addition, theapparatus further includes: a second map generation module, configuredto generate a second raster map having a second resolution by mergingrasters in the first raster map, the second resolution being lower thanthe first resolution; and a map storage module, configured to store thefirst raster map and an association between the first raster map and thesecond raster map.

In a third aspect, the present disclosure provides a computing device,the computing device including one or more processors; and a storageapparatus, for storing one or more programs. The one or more programs,when executed by the one or more processors, cause the computing deviceto implement the method or process according to some embodiments of thepresent disclosure.

In a fourth aspect, the present disclosure provides a computer readablemedium, storing a computer program thereon, the computer program, whenexecuted by a processor, implements the method or process according tosome embodiments of the present disclosure.

It should be appreciated that the content described in the Summary ofthe Invention is not intended to limit the key or important features ofsome embodiments of the present disclosure, and is not intended to limitthe scope of the present disclosure. Other features of the presentdisclosure will be readily understood by the following description.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other characteristics, advantages, and aspects ofembodiments of the present disclosure will become more apparent byreferring to following detailed description in conjunction with theaccompanying drawings. In the accompanying drawings, the identical orsimilar reference numerals indicate the identical or similar elements,in which:

FIG. 1 shows a schematic diagram of an example environment in which someembodiments of the present disclosure can be implemented;

FIG. 2 shows a flowchart of a process for generating a raster mapaccording to some embodiments of the present disclosure;

FIG. 3A shows a schematic diagram of raster merging according to someembodiments of the present disclosure;

FIG. 3B shows another schematic diagram of raster merging according tosome embodiments of the present disclosure;

FIG. 4 shows a schematic diagram of an octree spatial index according tosome embodiments of the present disclosure;

FIG. 5 shows a flowchart of a process for invoking a raster mapaccording to some embodiments of the present disclosure;

FIG. 6 shows a block diagram of an apparatus for generating a raster mapaccording to some embodiments of the present disclosure; and

FIG. 7 shows a block diagram of a computing device capable ofimplementing various embodiments of the present disclosure.

DETAILED DESCRIPTION OF EMBODIMENTS

Embodiments of the present disclosure will be described in more detailbelow by referring to the accompanying drawings. Although someembodiments of the present disclosure are shown in the drawings, itshould be understood that the present disclosure may be implemented invarious forms, and should not be construed as limited to the embodimentsset forth herein. Rather, these embodiments are provided to understandthe present disclosure more thoroughly and completely. It should beunderstood that the accompanying drawings and some embodiments of thepresent disclosure are only used as examples, rather than limiting thescope of protection of the present disclosure.

In the description on some embodiments of the present disclosure, theterm “include” and wordings similar to the term should be understood asopen-ended, i.e., “including but not limited to.” The term “based on”should be understood as “at least partially based on.” The term “oneembodiment” or “the embodiment” should be understood as “at least oneembodiment.” The terms, such as “first,” and “second,” may refer todifferent or identical objects. Other explicit and implicit definitionsmay also be included hereinafter.

The raster map is a high-precision map that can provide higher precisionthan that of ordinary navigation maps. However, a traditional raster maptypically only provides map data with one resolution. That is, there isonly a single-scale raster map. Therefore, the traditional raster mapcannot meet navigation or positioning services at different demandlevels (e.g., different precision). In addition, the traditional rastermap faces the problem that the old and new data are difficult toregister when updating, causing difficulty in updating the raster map.Thus, the raster map is usually updated in a completely updatedapproach, which consumes a large amount of storage and computingresources and time cost. In addition, each of the rasters in theconventional raster map usually has only one attribute information ofwhether it is occupied, and the amount of information of the raster issmall, so that the navigation and positioning performance are also weak.

In order to solve at least one of the above problems, some embodimentsof the present disclosure propose a method and apparatus for generatinga roaster map. Some embodiments of the present disclosure are capable ofmeeting navigation or positioning requirements at different levels bygenerating raster maps of multiple resolutions. At the same time, someembodiments of the present disclosure store only the raster map havingthe highest resolution, rather than directly storing raster maps oflower resolutions, thereby saving the storage space. In addition, someembodiments of the present disclosure update the raster map by applyinga point cloud registration method, thereby enabling the effect of apartial update of the map. In addition, each raster in the raster mapmay be extended to add other attributes according to requirements, inaddition to including the traditional information of whether beingoccupied, thereby improving navigation and positioning capabilities.Some illustrative embodiments of the present disclosure will bedescribed in detail below with reference to FIGS. 1-7.

FIG. 1 shows a schematic diagram of an example environment 100 in whichsome embodiments of the present disclosure can be implemented. In theexample environment 100, a data acquisition body, in this case a vehicle120, is traveling on a road 110. The vehicle 120 has a laser acquisitiondevice 125 affixed thereto that is capable of acquiring spatial data ofthe surrounding environment using a lidar. The vehicle 120 may be drivenby a driver to acquire data on the road 110 in accordance with apredetermined route and/or acquisition cycle. Of course, the driver mayalso autonomously determine the route of acquisition and/or acquisitioncycle. The vehicle 120 may be a common personal vehicle or a dedicatedacquisition vehicle, or any other suitable vehicle.

The laser acquisition device 125 has a laser scanner that may acquiredata of the surrounding environment (e.g., identify location of thesurrounding objects, types, reflectivity, densities, curvatures, etc. ofthe objects) during travelling of the vehicle 120, thus forming laserpoint cloud (such as point cloud 128 shown in FIG. 1). In theembodiments described herein, the laser point cloud refers to a set ofmass points representing the spatial distribution of the target obtainedby acquiring the spatial coordinates of each sample point on the surfaceof the object in the environment.

In some embodiments, the laser acquisition device 125 may be an airbornelidar system with light detection and ranging (LiDAR) functionality thatutilizes a global positioning system (GPS) and an inertial measuringunit (IMU) to measure the three-dimensional coordinates of the object inthe environment. The laser point cloud acquired by LiDAR has theadvantages of high data precision, high data density, strong penetratingability, and strong anti-interference ability. It should be understoodthat the vehicle 120 and the laser acquisition device 125 may becollectively referred to as a laser acquisition entity, a laseracquisition vehicle, and the like. Moreover, the positioning system isnot limited to the GPS. The Galileo satellite positioning system ofEurope, the Beidou satellite positioning system of China, etc. may allbe used in combination with some embodiments of the present disclosure.

As shown in FIG. 1, the environment 100 further includes a mapgeneration module 130, a map-updating module 140, and a map database150. The map generation module 130 may generate a raster map, whichtypically includes a plurality of rasters, based on the laser pointcloud obtained by the laser acquisition device 125, and stores theraster map in the map database 150. The map-updating module 140 mayobtain updated laser point cloud and update the data in the map database150 by registering with the laser point cloud prior to the update (e.g.,partial update may be implemented). The generated raster map (e.g., theraster map 155) is stored and managed in the map database 150. In theraster map 155, a black raster indicates that the raster is alreadyoccupied, indicating that there is an obstacle at the correspondingposition, and a white raster indicates that there is no obstacle at thecorresponding position. In some embodiments, the map generation module130, the map-updating module 140, and the map database 150 may beintegrated into a single computing device, collectively referred to asthe computing device. Alternatively, the map generation module 130, themap-updating module 140, and the map database 150 may also be arrangedseparately across multiple devices.

In some embodiments, alternatively, the map generation module 130 may belocally connected to the laser acquisition device 125. For example, themap generation module 130 may also be deployed inside the vehicle 120.Alternatively, the map generation module 130 may be remotely connectedto the laser acquisition device 125, such as via a wireless network. Inaddition, the laser point cloud acquired by the laser acquisition device125 may also be first stored in the storage device. Then, the mapgeneration module 130 obtains the laser point cloud from the storagedevice. Some embodiments of the present disclosure have no limitationswith respect to how the map generation module 130 obtains the laserpoint cloud.

As shown in FIG. 1, the map generation module 130 may generate theraster map 155 based on the acquired laser point cloud, for example thelaser point cloud 128, and store the raster map 155 in the map database150 for invocation. According to some embodiments of the presentdisclosure, the map generation module 130 may also generate raster mapsof multiple resolutions and store only the raster map having the highestresolution directly in the map database 150.

It should be understood by those skilled in the art that although anexample of acquiring the laser point cloud on the road 110 is shown inthe environment 100 of FIG. 1, the laser point cloud may also beacquired from other scenarios, for example, acquiring laser point clouddata indoor. In an indoor acquisition scenario, the acquired laser pointcloud may be used for the navigation or positioning of indoor robots. Inaddition, although FIG. 1 shows that the three-dimensional spatialcoordinates in the environment are acquired, it is also possible toacquire, for example, indoor two-dimensional plane coordinates, fornavigation and positioning of robots (for example, indoor sweepingrobots) and the like.

FIG. 2 shows a flowchart of a process 200 for generating a raster mapaccording to some embodiments of the present disclosure. It should beunderstood that the process 200 may be performed by the map generationmodule 130 described above with reference to FIG. 1.

At block 204, generating a first raster map having a first resolutionbased on acquired laser point cloud. For example, the map generationmodule 130 may obtain a three-dimensional laser point cloud from thelaser acquisition device 125. In general, point clouds acquired usingdepth cameras and ordinary sensors are not as dense and accurate aslaser point clouds, and cannot meet the demand for fine navigation andpositioning. In some embodiments, the map generation module 130 mayfirst filter noise from the laser point cloud and then segment the laserpoint cloud at a predetermined resolution. For example, whether a pointin a raster is a noise point may be determined based on the spatialneighborhood relationship between the raster maps, and the specific sizeof the raster map is determined based on the average point distance.

In some embodiments, a spatial grid containing laser point clouds may befirst established and each raster may be set to a predetermined size(e.g., 0.125 meters or other size). If there are one or more points inthe point cloud at a location corresponding to a raster, the raster maybe marked as occupied; on the contrary, if there is no point at thecorresponding location of the raster, the raster is marked asunoccupied, thereby enabling marking of each raster in the spatial grid.

In general, the smaller the size of each raster is, the higher itsaccuracy is and the higher the resolution is. That is to say, for thesame spatial grid, the more the rasters are, the higher the resolutionof the spatial grid is. When some embodiments of the present disclosurerefer to the size of a raster of a predetermined size as the highestresolution, it represents the highest resolution in the case of such apredetermined size, and does not represent the highest resolution in allcases.

In some embodiment, a multi-dimensional attribute of each of the rastersin the first raster map may be generated. Compared with the traditionaltechnology, each of the rasters in the raster map may be extended to addother attributes according to requirements, in addition to including thetraditional occupy attribute of whether being occupied, therebyproviding navigation and positioning capabilities. In some embodiments,the multi-dimensional attribute may include an average reflectivityattribute, from which the material of the obstacle in the environmentmay be determined. In some embodiments, the multi-dimensional attributemay include a density attribute, from which the type of the obstacle maybe determined. In some embodiments, the multi-dimensional attribute mayinclude a curvature attribute. Based on the curvature attribute, thecharacteristic of the curved surface of the obstacle may be fitted,which is more suitable for navigation and positioning in thethree-dimensional space.

In some embodiments, the multi-dimensional attribute may also include acolor attribute that represents the color of the obstacle. The colorattribute may be generated based on the laser point cloud and itscorresponding photo. The color of a point is determined, for example, byidentifying the value of the photo's pixel corresponding to the point inthe laser point cloud, thereby providing powerful navigation andpositioning capabilities.

At block 206, generating a second raster map having a second resolutionby merging rasters in the first raster map, the second resolution beinglower than the first resolution. In some embodiments, after generatingthe first raster map having the highest resolution, the map generationmodule 130 may merge a fixed number of rasters in the first raster mapinto one raster, and may provide a second raster map having a lowerresolution using this method.

For example, in three-dimensional space, every eight or 27 rasters orthe like may be merged into one raster; and in two-dimensional space,every 4 or 9 rasters or the like may be merged into one raster. Eachmerged raster has an attribute, which may be determined based on theattributes of the plurality of rasters being merged. For example, if oneor more of the multiple rasters are occupied, the merged single rastermay be determined to be occupied.

In some embodiments, in order to provide more raster maps havingdifferent resolutions, rasters in the second raster map may also bemerged to generate a third raster map having a third resolution. Inaddition, rasters in the third raster map may be further merged asneeded. Some illustrative embodiments of merging the rasters aredescribed below with reference to FIGS. 3A, 3B, and 4.

At block 208, storing the first raster map and an association betweenthe first raster map and the second raster map. For example, aftergenerating the raster maps of multiple resolutions (e.g., the firstraster map and the second raster map), the map generation module 130stores the first raster map in the map database 150. Moreover, for thesecond raster map having a lower resolution, some embodiments of thepresent disclosure do not store the second raster map itself, butinstead store an association between the first raster map and the secondraster map (e.g., the spatial index between the two raster maps), suchthat the second raster map is dynamically generated by the first rastermap and the association, saving storage space in the map database.

As will be appreciated from the above description, the process 200according to some embodiments of the present disclosure are capable ofmeeting different levels of navigation or positioning requirements bygenerating raster maps of multiple resolutions. At the same time, someembodiments of the present disclosure store only the raster map havingthe highest resolution, rather than directly storing raster maps oflower resolutions, thereby saving the storage space.

In some embodiments, when an update to the map database is required, themap-updating module 140 may obtain updated laser point cloud andregister the updated laser point cloud with the pre-update laser pointcloud by adjusting the coordinate system of the updated laser pointcloud to coincide with the coordinate system of the pre-update laserpoint cloud, thereby updating the map database using the registeredupdated laser point cloud. According to some embodiments of the presentdisclosure, updating the raster map by applying a point cloudregistration method may update only a part of the first raster map,thereby achieving the effect of a partial update of the map. It shouldbe understood that in the embodiments according to the presentdisclosure, since only the raster map having the highest resolution isstored in the map database 150, the update is performed at the highestresolution when the map is updated.

In some embodiments, in the process of point cloud registration, anobjective function for all corresponding points may be set first, andthe updated laser point cloud is transformed by a rotation andtranslation matrix. For example, the transformed laser point cloud maybe compared with the original laser point cloud. As long as there aretwo points with a distance less than the threshold in the two pointclouds, the two points are considered to be corresponding points. Afterobtaining a set of corresponding points, the rotation and translationmay be estimated based on the corresponding points. Next, the discoveryof the corresponding points and the estimation of the rotation andtranslation may be performed iteratively until convergence. That is tosay, the rotation and translation may be fixed first to find the optimalcorresponding points by using the nearest neighbor algorithm, and thenthe optimal corresponding points are fixed to optimize the rotation andtranslation, so that the value of the objective function is continuouslyreduced until convergence, thereby completing the registration betweenthe point clouds.

FIG. 3A shows a schematic diagram 300 of raster merging according tosome embodiments of the present disclosure. As shown in FIG. 3A, theraster map in a first-level raster 310 is the highest resolution map,which is stored in the map database. According to some embodiments ofthe present disclosure, every eight rasters in the first-level raster310 (2 in length, width and height in the stereo space) may be mergedinto one raster, thereby generating a second-level raster 320. Everyeight rasters in the second-level raster 320 may further be merged intoone raster, thereby generating a third-level raster 330. During theraster merging, the multi-dimensional attribute is re-determined foreach merged raster. For example, for the occupy attribute, if one ormore occupied rasters exist in the eight lower-level rasters, the mergedupper-level raster is determined to be occupied. On the contrary, ifthere is no occupied raster in the eight lower-level rasters, the mergedupper-level raster is determined to be unoccupied, as shown in FIG. 3A.

FIG. 3B shows another schematic diagram 350 of raster merging accordingto some embodiments of the present disclosure. As shown in FIG. 3B, theraster map in a first-level raster 360 is the highest resolution map,which is stored in the map database. According to some embodiments ofthe present disclosure, every twenty-seven rasters in the first-levelraster 360 (3 in length, width and height in the stereo space) may bemerged into one raster, thereby generating a second-level raster 370.During the raster merging, the multi-dimensional attribute isre-determined for each merged raster. For example, for the occupyattribute, if one or more occupied rasters exist in the twenty-sevenlower-level rasters, the merged upper-level raster is determined to beoccupied. On the contrary, if there is no occupied raster in thetwenty-seven lower-level rasters, the merged upper-level raster isdetermined to be unoccupied, as shown in FIG. 3B.

FIG. 4 shows a schematic diagram 400 of an octree spatial indexaccording to some embodiments of the present disclosure. For example, anoctree spatial index is used to establish the association between rastermaps of different resolution levels. As shown in FIG. 4, a node 410 maycorrespond to a raster in the raster map 419, and have eight branchnodes 421, 422, 423, 424, 425, 426, 427, and 428, each of whichcorresponds to a raster in the raster map 429. That is, the rastercorresponding to the node 410 is generated by merging the eight rasterscorresponding to the nodes 421, 422, 423, 424, 425, 426, 427, and 428.The node corresponding to each raster in the raster map 429 also haseight branch nodes. For example, the node 423 has eight branch nodes4231, 4232, 4233, 4234, 4235, 4236, 4237, and 4238, each of whichcorresponds to a raster in a raster map 4239. In this way, based on theraster map 4239 of the highest resolution (which has the largest numberof rasters and the highest resolution, as described above), the rastermap 429 of the lower resolution and the raster map 419 of the lowestresolution may be quickly determined by the octree spatial index. Whenthe map is invoked, it may be possible to quickly switch between theseraster maps of different resolution according to the required resolutionto meet the navigation and positioning requirements of differentresolutions.

FIG. 5 shows a flowchart of a process 500 for invoking a raster mapaccording to some embodiments of the present disclosure. It should beunderstood that the process 500 may be performed by the map generationmodule 130 or a storage scheduling module in the map database 150described above with reference to FIG. 1.

At block 502, a request for a digital map is received, for example, inan autonomous driving scenario or an indoor robot navigation scenario,receiving a scheduling request by the computing device for the rastermap.

At block 504, a determination is made as to whether the request relatesto the first raster map, i.e., a raster map of the highest resolution.If it is determined that the request relates to the first raster map,since the first raster map already exists in the map database, then atblock 506, the first raster map may be obtained directly from the mapdatabase (e.g., the map database 150).

If it is determined at block 504 that the request involves the rastermap other than the first raster map, then at block 508, a determinationis made as to whether the request relates to the second raster map. Ifso, since the second raster map is not the map of the highestresolution, it is not stored directly in the map database 150, then atblock 510, the first raster map and the association between the firstraster map and the second raster map (e.g., the spatial index) areobtained from the map database 150. At block 512, the second raster mapis dynamically generated based on the first raster map and theassociation between the first raster map and the second raster map.

On the other hand, if it is determined at block 508 that the request isnot related to the second raster map, then at block 514, it isdetermined whether the request relates to the third raster map of alower resolution level. If it is determined that the request relates tothe third raster map, since the third raster map is not the map of thehighest resolution, it is not stored directly in the map database, thenat block 516, the first raster map, the association between the firstraster map and the second raster map, and the association between thesecond raster map and the third raster map are obtained from the mapdatabase. Then at block 518, the third raster map is dynamicallygenerated based on the first raster map, the association between thefirst raster map and the second raster map, and the association betweenthe second raster map and the third raster map.

By means of the above process, the raster maps can be retrieved step bystep in descending order of resolution, in response to the request for amap. Of course, this is not obligatory. For example, in some alternativeembodiments, an association index between the first raster map and thethird raster map may also be generated directly, thereby generating thethird raster map directly without the second raster map. Further, in theprocess 500, if the request does not involve the third raster map, thenother processing may be performed.

According to some embodiments of the present disclosure, generating thesecond raster map from the first raster map or generating the thirdraster map from the first raster map is very fast by using the octreespatial index, thereby ensuring the timeliness of map invoking.

FIG. 6 shows a block diagram of an apparatus 600 for generating a rastermap according to some embodiments of the present disclosure. As shown inFIG. 6, the apparatus 600 includes a first map generation module 620, asecond map generation module 630, and a map storage module 640. Thefirst map generation module 620 is configured to generate a first rastermap having a first resolution based on acquired laser point cloud. Insome embodiments, the first map generation module 620 may include apoint cloud acquisition module (not shown) for obtaining a laser pointcloud acquired by a laser acquisition entity. In addition, the secondmap generation module 630 is configured to generate a second raster maphaving a second resolution by merging rasters in the first raster map,the second resolution being lower than the first resolution. The mapstorage module 640 is configured to store the first raster map and anassociation between the first raster map and the second raster map. Insome embodiments, the apparatus 600 further includes a third mapgeneration module (not shown), configured to generate a third raster maphaving a third resolution by merging rasters in the second raster map,the third resolution being lower than the second resolution.

It should be understood that the first map generation module 620, thesecond map generation module 630, and the map storage module 640 shownin FIG. 6 may be included in the map generation module 130 describedwith reference to FIG. 1. Moreover, it should be understood that themodules illustrated in FIG. 6 may perform steps or actions in the methodor process with reference to some embodiments of the present disclosure.

FIG. 7 shows a schematic block diagram of an illustrative device 700capable of implementing various embodiments of the present disclosure.The device 700 may be used to implement the apparatus 600 for generatinga raster map of the present disclosure. As shown in the figure, thedevice 700 includes a central processing unit (CPU) 701 that may performvarious appropriate actions and processing in accordance with computerprogram instructions stored in a read only memory (ROM) 702 or computerprogram instructions loaded into a random access memory (RAM) 703 from astorage unit 708. In the RAM 703, various programs and data required forthe operation of the device 700 may also be stored. The CPU 701, the ROM702, and the RAM 703 are connected to each other through a bus 704. Aninput/output (I/O) interface 705 is also coupled to the bus 704.

A plurality of components in the device 700 are coupled to the I/Ointerface 705, including: an input unit 706, such as a keyboard or amouse; an output unit 707, such as various types of displays, orspeakers; the storage unit 708, such as a disk or an optical disk; and acommunication unit 709 such as a network card, a modem, or a wirelesscommunication transceiver. The communication unit 709 allows the device700 to exchange information/data with other devices over a computernetwork such as the Internet and/or various telecommunication networks.

The processing unit 701 performs the various methods and processesdescribed above, such as the process 200 and/or the process 500. Forexample, in some embodiments, the process 200 and/or the process 500 maybe implemented as a computer software program that is tangibly embodiedin a machine readable medium, such as the storage unit 708. In someembodiments, some or all of the computer programs may be loaded and/orinstalled onto the device 700 via the ROM 702 and/or the communicationunit 709. When a computer program is loaded into the RAM 703 andexecuted by the CPU 701, one or more of the actions or steps of theprocess 200 and/or the process 500 described above may be performed.Alternatively, in other embodiments, the CPU 701 may be configured toperform the process 200 and/or the process 500 by any other suitablemeans (e.g., by means of firmware).

The functions described herein above may be performed, at least in part,by one or more hardware logic components. For example, and withoutlimitation, illustrative types of hardware logic components that may beused include: Field Programmable Gate Array (FPGA), Application SpecificIntegrated Circuit (ASIC), Application Specific Standard Product (ASSP),System on Chip (SOC), Complex Programmable Logic Device (CPLD), and thelike.

Program codes for implementing the method of the present disclosure maybe written in any combination of one or more programming languages.These program codes may be provided to a processor or controller of ageneral purpose computer, special purpose computer or other programmabledata processing apparatus such that the program codes, when executed bythe processor or controller, enables the functions/operations specifiedin the flowcharts and/or block diagrams being implemented. The programcodes may execute entirely on the machine, partly on the machine, as astand-alone software package partly on the machine and partly on theremote machine, or entirely on the remote machine or server.

In the context of the present disclosure, the machine readable mediummay be a tangible medium that may contain or store programs for use byor in connection with an instruction execution system, apparatus, ordevice. The machine readable medium may be a machine readable signalmedium or a machine readable storage medium. The machine readable mediummay include, but is not limited to, an electronic, magnetic, optical,electromagnetic, infrared, or semiconductor system, apparatus, ordevice, or any suitable combination of the foregoing. More specificexamples of the machine readable storage medium may include anelectrical connection based on one or more wires, portable computerdisk, hard disk, random access memory (RAM), read only memory (ROM),erasable programmable read only memory (EPROM or flash memory), opticalfiber, portable compact disk read only memory (CD-ROM), optical storagedevice, magnetic storage device, or any suitable combination of theforegoing.

In addition, although various actions or steps are described in aspecific order, this should not be understood that such actions or stepsare required to be performed in the specific order shown or insequential order, or all illustrated actions or steps should beperformed to achieve the desired result. Multitasking and parallelprocessing may be advantageous in certain circumstances. Likewise,although several specific implementation details are included in theabove discussion, these should not be construed as limiting the scope ofthe present disclosure. Certain features described in the context ofseparate embodiments may also be implemented in combination in a singleimplementation. Conversely, various features described in the context ofa single implementation may also be implemented in a plurality ofimplementations, either individually or in any suitable sub-combination.

Although some embodiments of the present disclosure are described inlanguage specific to structural features and/or method logic actions, itshould be understood that the subject matter defined in the appendedclaims is not limited to the specific features or actions describedabove. Instead, the specific features and actions described above aremerely illustrative forms of implementing the claims.

What is claimed is:
 1. A method for generating a raster map, the methodcomprising: generating a first raster map having a first resolutionbased on acquired laser point cloud; generating a second raster maphaving a second resolution by merging rasters in the first raster map,the second resolution being lower than the first resolution; and storingthe first raster map and an association between the first raster map andthe second raster map.
 2. The method according to claim 1, furthercomprising: establishing the association between the first raster mapand the second raster map using an octree spatial index.
 3. The methodaccording to claim 1, further comprising: generating the second rastermap using the stored association and the first raster map, in responseto a digital map request relating to the second raster map.
 4. Themethod according to claim 1, further comprising: generating a thirdraster map having a third resolution by merging rasters in the secondraster map, the third resolution being lower than the second resolution;and storing the association between the second raster map and the thirdraster map.
 5. The method according to claim 1, wherein the generatingthe first raster map comprises: generating a multi-dimensional attributeof each of the rasters in the first raster map, the multi-dimensionalattribute comprising an occupancy attribute indicating whether a rasterbeing occupied and at least one of: an average reflectivity attribute, acolor attribute, a density attribute, or a curvature attribute.
 6. Themethod according to claim 5, wherein the color attribute is generatedbased on the laser point cloud and a photo associated with the laserpoint cloud.
 7. The method according to claim 1, further comprising:acquiring updated laser point cloud; registering the updated laser pointcloud with the laser point cloud by adjusting a coordinate system of theupdated laser point cloud based on the coordinate system of the laserpoint cloud; and updating the first raster map using the registeredupdated laser point cloud.
 8. The method according to claim 7, whereinthe updated laser point cloud is associated with a part of the laserpoint cloud, and the updating the first raster map comprises: updatingthe part of the first raster map using the registered updated laserpoint cloud.
 9. An apparatus for generating a raster map, the apparatuscomprising: at least one processor; and a memory storing instructions,the instructions when executed by the at least one processor, cause theat least one processor to perform operations, the operations comprising:generating a first raster map having a first resolution based onacquired laser point cloud; generating a second raster map having asecond resolution by merging rasters in the first raster map, the secondresolution being lower than the first resolution; and storing the firstraster map and an association between the first raster map and thesecond raster map.
 10. The apparatus according to claim 9, wherein theoperations further comprise: establishing the association between thefirst raster map and the second raster map using an octree spatialindex.
 11. The apparatus according to claim 9, wherein the operationsfurther comprise: generating the second raster map using the storedassociation and the first raster map, in response to a digital maprequest relating to the second raster map.
 12. The apparatus accordingto claim 9, wherein the operations further comprise: generating a thirdraster map having a third resolution by merging rasters in the secondraster map, the third resolution being lower than the second resolution;and storing the association between the second raster map and the thirdraster map.
 13. The apparatus according to claim 9, wherein thegenerating the first raster map comprises: generating amulti-dimensional attribute of each of the rasters in the first rastermap, the multi-dimensional attribute comprising an occupancy attributeindicating whether a raster being occupied and at least one of: anaverage reflectivity attribute, a color attribute, a density attribute,or a curvature attribute.
 14. The apparatus according to claim 13,wherein the color attribute is generated based on the laser point cloudand a photo associated with the laser point cloud.
 15. The apparatusaccording to claim 9, wherein the operations further comprise: acquiringupdated laser point cloud; registering the updated laser point cloudwith the laser point cloud by adjusting a coordinate system of theupdated laser point cloud based on the coordinate system of the laserpoint cloud; and updating the first raster map using the registeredupdated laser point cloud.
 16. The apparatus according to claim 15,wherein the updated laser point cloud is associated with a part of thelaser point cloud, and the updating the first raster map comprises:updating the part of the first raster map using the registered updatedlaser point cloud.
 17. A non-transitory computer-readable storage mediumstoring a computer program, the computer program when executed by one ormore processors, causes the one or more processors to performoperations, the operations comprising: generating a first raster maphaving a first resolution based on acquired laser point cloud;generating a second raster map having a second resolution by mergingrasters in the first raster map, the second resolution being lower thanthe first resolution; and storing the first raster map and anassociation between the first raster map and the second raster map.